1. Technical Field
The present invention relates generally to search engines, and more particularly, to a search engine for a knowledge base that is capable of determining a match answer and an alternative answer based on a history record of cumulative probability values.
2. Related Art
Conventional search engines are located on a server side of a client-server environment. As a result, application of these search engines relative to knowledge bases that are located client-side is very difficult. For example, a knowledge base loaded to a portable digital assistant is incapable of searching unless communicable with a server-side search engine. Even if the client-side is readily communicable with the server-side search engine, processing delays such as database or application server requests (from client to server) affect performance. Performance problems are generally related to the Javascript or Perl front-end loaded nature of conventional server side systems and their related back-end DB2 or Oracle servers.
Conventional search-engines also do not address locating exact information that a user requests since they apply very complex layers of software abstraction, e.g. the Berkley search engine strategy and artificial intelligence algorithms.
Other disadvantages of conventional search engines is their inability to learn from prior searches for a user relative to a given knowledge base. That is, they do not readily provide user preferences relative to a knowledge base.
In view of the foregoing, there is a need in the art for a search engine that is client-side, high performance and learns user preferences.